Defining the Difference between Parameters & Statistics

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  • 0:01 Using Statistics To…
  • 0:25 Understanding…
  • 1:55 Parameters & Statistics
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Lesson Transcript
Instructor: Cathryn Jackson

Cat has taught a variety of subjects, including communications, mathematics, and technology. Cat has a master's degree in education and is currently working on her Ph.D.

Using data to describe information can be tricky. The first step is knowing the difference between populations and samples, and then parameters and statistics.

Using Statistics To Understand Populations

Lenae is campaigning for town mayor. Today, she is doing a little market research to understand the concerns of the people in her town. In order to collect this information, Lenae will have to understand parameters and statistics when working with populations.

In this lesson, you will learn about the differences between parameters and statistics when working with data. But first, let's review populations and samples.

Understanding Populations & Samples

A population is all members of a specified group. For example, in Lenae's case she is collecting data on a very literal population, the population of her town. All members of this town would be included in the population. However, most of the time it isn't practical to get information from every member of a population.

When this happens, we have to find a different way of getting information that represents the population without actually asking the whole population. Lenae will probably not have the time and resources to collect information from the entire town; therefore, she will need another approach to getting the information she needs. She will need a sample to gather this information.

A sample is a part of a population used to describe the whole group. For example, Lenae could go to a local event or mail out surveys to the people in her town. As long as the information she collects is from the town and not a neighboring community, then this can count as Lenae's sample group.

Samples are used to help the data researcher, in this case Lenae, to understand the entire population. There are many different ways you can get a sample from your population. These include:

  • Random sampling
  • Simple random sampling
  • Cluster sampling
  • Stratified sampling
  • Systematic sampling

You'll learn more about each of these types of sampling in future lessons!

Now that you understand population and samples, let's discuss how they relate to parameters and statistics.

Parameters & Statistics

Lenae has collected the information she needs from her sample. Now it is time to analyze this information using the concepts of parameters and statistics.

A parameter is the characteristics used to describe a population. For example, Lenae knows one parameter of her population is that they all live in the same town. This is a 100% known parameter of the population. If Lenae was able to see a 100% accurate census in the town, she could probably find parameters such as the number of people in a certain age range in the population. It's hard to have 100% proof for particular characteristics of a population. This is when we use statistics.

A statistic is the characteristics of a sample used to infer information about the population. For example, Lenae is using a sample to analyze data about her town's population. Lenae has found that 64% of the people she surveyed are concerned about the safety of the town's parks. Lenae can use this statistic to infer that approximately 64% of the town is also concerned about the safety of the town's parks.

Now that you understand parameters and statistics, let's practice by identifying the two.

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